System and method for motion estimation and compensation in helical computed tomography

ABSTRACT

An improved system and method for estimating and compensating for motion by reducing motion artifacts produced during image reconstruction from helical computed tomography (CT) scan data. In a particular embodiment, the reconstruction may be based on helical partial angle reconstruction (PAR).

CROSS-REFERENCE TO RELATED APPLICATIONS

This application claims priority to U.S. Provisional Patent ApplicationNo. 62/423,166 entitled, “System and Method for Motion Estimation andCompensation in Helical Computed Tomography”, filed on Nov. 16, 2017,which is incorporated by reference in its entirety.

BACKGROUND OF THE INVENTION

The present invention relates to the field of image processing, and inparticular to image processing in medical applications. In particular,the present invention is directed to a method for motion estimation andmotion compensation of a helical computed tomography (CT) scan of anobject of interest.

Motion is one of the most critical sources of artifacts in helicalcone-beam computed tomography (CT). Motion artifacts result fromdiscrepancies between the requirement that the object remain unchangedduring the scan and reality, in which the object changes (“deforms” or“moves”) during the scan. Motion of the patient, whether voluntary orinvoluntary, during image acquisition may result in motion artifacts inthe reconstructed image. Involuntary motion, such as respiration orcardiac motion, may result in motion artifacts. While there aretechniques known in the art for the reconstruction of motion compensatedimages from circular CT scan data, the known techniques do not addressthe unique conditions of a helical CT scan, wherein the field of view(FOV) is continuously changing.

Accordingly, what is needed in the art is an improved system and methodfor motion estimation and compensating for motion by reducing motionartifacts produced during image reconstruction from helical computedtomography (CT) scan data.

SUMMARY OF THE INVENTION

The present invention provides an improved system and method forestimating motion and compensating for motion by reducing motionartifacts produced during image reconstruction from helical computedtomography scan data. In various embodiments, the system and method canalso be applied to more general helical-like trajectories, includingvariable pitch helices and helices in which the axis of rotationchanges.

In one embodiment, the present invention provides a method forestimating and compensating for motion by reducing motion artifacts inan image reconstruction from helical computed tomography (CT) scan dataof an object of interest, which includes, collecting helical computertomography (CT) scan data of an object of interest, wherein the scandata is acquired using a radiation source to generate a cone beam and aradiation detector to detect the cone beam. The method further includes,selecting a plurality of center-points along a trajectory of theradiation source and identifying a plurality of pairs of sections alongthe trajectory of the radiation source, wherein each of the plurality ofpairs of sections is associated with one of the plurality ofcenter-points and wherein a first section of each of the pairs ofsections and a second section of each of the pairs of sections arepositioned on opposite sides of the center-point. In a particularembodiment, the sections are separated from each other by an angulardistance equal to π. The method additionally includes, selecting asubset of the plurality of pairs of sections and reconstructing, foreach pair of the subset, a first partial image from the scan data of thefirst section and a second partial image from the scan data of thesecond section and performing image registration of the first partialimage and the second partial image for each pair of the subset toestimate a deformation that transforms the first partial image into thesecond partial image, wherein the deformation is representative ofmotion of the object of interest during the scan. Following imageregistration of the partial images, the method further includes,generating a motion compensated image by reconstructing the object ofinterest using the scan data and the estimated deformation.

In an additional embodiment, the invention provides a system forestimating and compensating for motion by reducing motion artifacts inan image reconstruction from helical computed tomography (CT) scan dataof an object of interest. The system includes, a memory for storing ahelical computer tomography (CT) scan data of an object of interest anda data processor. The data processor is configured for estimating andcompensating for motion by reducing motion artifacts in an imagereconstruction from the helical computed tomography (CT) scan data of anobject of interest. As such, the data processor is adapted for loadingthe helical CT scan data from the memory, selecting a plurality ofcenter-points along a trajectory of the radiation source and identifyinga plurality of pairs of sections along the trajectory of the radiationsource, wherein each of the plurality of pairs of sections is associatedwith one of the plurality of center-points and wherein a first sectionof each of the pairs of sections and a second section of each of thepairs of sections are positioned on opposite sides of the center-point.In a particular embodiment, the sections are separated from each otherby an angular distance equal to π. The data processor is furtherconfigured for selecting a subset of the plurality of pairs of sectionsand for reconstructing, for each pair of the subset, a first partialimage from the scan data of the first section and a second partial imagefrom the scan data of the second section, for performing imageregistration of the first partial image and the second partial image foreach pair of the subset to estimate a deformation that transforms thefirst partial image into the second partial image, wherein thedeformation is representative of motion of the object of interest duringthe scan, for generating a motion artifact compensated image byreconstructing the object of interest using scan data and the estimateddeformation.

The present invention additionally provides an embodiment including oneor more non-transitory computer-readable media havingcomputer-executable instructions for performing a method of estimatingand compensating for motion by reducing motion artifacts in an imagereconstruction from helical computed tomography (CT) scan data of anobject of interest. The method includes, collecting helical computertomography (CT) scan data of an object of interest, wherein the scandata is acquired using a radiation source to generate a cone beam and aradiation detector to detect the cone beam. The method further includes,selecting a plurality of center-points along a trajectory of theradiation source and identifying a plurality of pairs of sections alongthe trajectory of the radiation source, wherein each of the plurality ofpairs of sections is associated with one of the plurality ofcenter-points and wherein a first section of each of the pair ofsections and a second section of each of the pair of sections arepositioned on opposite sides of the center-point. In a particularembodiment, the sections are separated from each other by an angulardistance equal to π. The method additionally includes, selecting asubset of the plurality of pairs of sections and reconstructing, foreach pair of the subset, a first partial image from the scan data of thefirst section and a second partial image from the scan data of thesecond section and performing image registration of the first partialimage and the second partial image for each pair of the subset toestimate a deformation that transforms the first partial image into thesecond partial image, wherein the deformation is representative ofmotion of the object of interest during the scan. Following imageregistration of the partial images, the method further includes,generating a motion artifact compensated image by reconstructing theobject of interest using scan data and the estimated deformation.

BRIEF DESCRIPTION OF THE DRAWINGS

For a fuller understanding of the invention, reference should be made tothe following detailed description, taken in connection with theaccompanying drawings, in which:

FIG. 1 is an illustration of an exemplary helical computer tomography(CT) scanner, in accordance with an embodiment of the present invention.

FIG. 2 is an illustration of a portion of a helical trajectory andassociated section pairs for estimating motion artifacts in a helical CTscan, in accordance with an embodiment of the present invention. Thesource trajectory is shown projected onto the plane perpendicular to therotation axis.

FIG. 3 is an illustration of an auxiliary reconstruction volume forcompensating for motion by reducing motion artifacts, in accordance withan embodiment of the present invention. The illustrated volume isvisible from one source position.

FIG. 4 is an illustration of the overlap of volumes visible from thesection pairs for estimating motion artifacts in a helical CT scan, inaccordance with an embodiment of the present invention.

FIG. 5 is an illustration of the PI lines within the overlap volume, inaccordance with an embodiment of the present invention.

FIG. 6 is a flow diagram illustrating a method for motion estimation andcompensation in a helical CT scan, in accordance with an embodiment ofthe present invention.

DETAILED DESCRIPTION OF THE INVENTION

FIG. 1 illustrates an exemplary embodiment of a helical CT scannersystem 100 according to the present invention. This embodiment isintended to be exemplary and the present invention will be described asrelating to medical imaging. However, this is not intended to be limitedand various embodiments of the present invention may also be used forother purposes, such as baggage scanning for security and materialanalysis.

As shown in FIG. 1, a helical CT scanner system 100 includes a gantry102 which is rotatable around a rotational axis 105. The gantry 102carries a radiation source 110 that forms a cone shaped radiation beam115. The radiation beam 115 emitted from the radiation source 110 isfocused on an object of interest 120 positioned in the center of thegantry 102. A radiation detector 125 is positioned on the gantry 102opposite from the radiation source 110. The radiation detector 125comprises a plurality of detector elements for measuring the intensityof the cone shaped radiation beam 115 after it passes through the objectof interest 120.

During a scan of the object of interest 120, the radiation source 110and the radiation detector 125 are rotated with the gantry 102 in adirection indicated 145. The object of interest 120 is additionallypositioned on a movable table 130 which moves the object of interest 120along a direction parallel to the rotational axis 105 of the gantry 102.As such, helical scan trajectory is created around the object ofinterest 120 and helical CT scan data of the object of interest isobtained.

Following the helical scanning of the object of interest 120, theradiation detector 125 provides the collected helical CT scan data to adata processor 135. The data processor 135 is adapted for reconstructingan image from the measurements provided by the radiation detector 125.The image generated by the data processor 135 may then be provided to adisplay 140 for subsequent viewing.

The data processor 135 is additionally adapted to perform motionestimation and motion compensation to correct for motion in the scandata provided by the radiation detector 125. Motion estimation andcompensation may be performed by the data processor 135 as detailedbelow.

In the case of a relatively long helical scan trajectory C, each voxel{right arrow over (x)}=(x₁,x₂,x₃) is reconstructed using its own sectionof C, denoted as C({right arrow over (x)}). Suppose that the parametricdescription of C is {right arrow over (y)}(s). Let I({right arrow over(x)}) be the parametric interval corresponding to C({right arrow over(x)}). In a helical CT scan, usually, the source of radiation movesalong the scan trajectory C with a constant speed, so that the parameters may be identified with time. Let ƒ({right arrow over (x)}, s) denotethe dynamic object, wherein s represents time. It is therefore impliedthat for every voxel {right arrow over (x)}, the value of f isreconstructed not at some reference time s₀, which is the same for all{right arrow over (x)}, but at some time s_(eff)({right arrow over(x)}), wherein s_(eff)({right arrow over (x)}) is the midpoint of theinterval I({right arrow over (x)}). Accordingly, in the case of helicalscanning it is desired to reconstruct only the function ƒ({right arrowover (x)}, s_(eff)({right arrow over (x)})).

In a circular scan, the source “sees” the same FOV (field of view) atall times, and this allows one to reconstruct ƒ({right arrow over(x)},s_(eff)). In contrast, in a helical scan, the FOV constantlychanges. This explains the difference between a circular scan and ahelical scan and why a different motion artifact estimation andcompensation method is required.

With reference to FIG. 2, it is necessary to find a volume which can bereconstructed using two sections of the helix 200 located at a distanceπ apart. As shown in FIG. 2, referring to these two sections of thehelix by their corresponding parametric intervals as I⁻ and I₊, intervalI⁻ 205 is centered at the point s₀−π/2, 215 and the interval I₊ 210 iscentered at the point s₀+π/2 220. S 230 identifies the direction ofrotation of the scan. As a result of symmetry, if motion estimation (ME)is performed based on the partial angle constructions (PARs) computedfrom the two intervals, then the estimated motion model will correspondto the time s₀ 225.

Assume that Δ_(α) 235 represents the range of directions (in theparallel beam geometry) that is used for computing PARs, as shown inFIG. 2. Let Δ_(γ):=sin⁻¹ (r/R) be half the fan angle of the ROI (regionof interest), wherein r is center radius 240 and R 245 is thesource-to-center of rotation distance. As such,

I ⁻(s ₀):=[(s ₀−π/2)−(Δ_(α)/2+Δ_(γ)),(s ₀−π/2)+(Δ_(α)/2+Δ_(γ))]

I ⁻(s ₀):=[(s ₀+π/2)−(Δ_(α)/2+Δ_(γ)),(s ₀+π/2)+(Δ_(α)/2+Δ_(γ))]  (1)

Thus, the width of each s-interval is Δ_(α)+2Δ_(γ).

Once the mid-point s₀ is fixed, the desired volume is the set of points{right arrow over (x)} that are “visible” from all source positionssϵI_(±)(s₀). Let V(s) 305 denote the set of points visible when thesource is located at s 300, as shown in FIG. 3, then:

V ⁻(s ₀)=∪_(sϵI) ⁻ _((s) ₀ ₎ V(s),V ₊(s ₀)=∪_(sϵI) ₊ _((s) ₀ ₎ V(s)  (2)

Then, the desired volume is V_(overlap)(s₀)=V⁻(s₀)∩V₊(s₀). A verticalcross-section 400 through V_(overlap) (s₀), 405 is illustrated in FIG.4. Since it is desirable to run the scan with a high pitch value, it isclear that the volume V_(overlap)(s₀) 405 is located rather close to thePI lines 410, and additionally PI lines 500 in FIG. 5., with oneendpoint located inside I⁻(s₀), and the other endpoint located insideI₊(s₀), as illustrated by one such PI line in FIG. 4.

Letting L(a,b) be the PI line passing through the points {right arrowover (y)}(a), {right arrow over (y)}(b), the following surface S(s₀) 500(sometimes referred to as a “potato chip”) can be defined, as shown inFIG. 5:

$\begin{matrix}{{S\left( s_{0} \right)}:={U_{{t} < {\frac{\Delta_{\alpha}}{2} + \Delta_{\gamma}}}{{L\left( {{s_{0} - {\pi/2} - t},{s_{0} + {\pi/2} + t}} \right)}.}}} & (3)\end{matrix}$

The PI lines in (Eq. 3) have the following properties: their bottomendpoints are in I⁻(s₀) 205, their top endpoints are in I₊(s₀) 210, andthey are symmetric about s₀ 225. When the helical pitch is high,V_(overlap) (s₀) 405 is a fairly “thin” set containing S(s₀) 500. Assuch, the potato chips, S(s₀) 500 for different s₀ 225 do not intersect.

Based on the previous discussion, the present invention provides amethod for motion estimation, which includes, first, choose a set ofequispaced points, s_(l),l=1, 2, . . . , L, covering the entire scanlength and denote the reconstruction grid as (x_(i),y_(j),z_(k)).

Second, perform motion estimation, which includes:

-   -   1) Loop over all s_(l). For each s_(l) repeat the following        steps.    -   2) For each (x_(i),y_(j)), find z_(ij)=z(x_(i),y_(j),s_(l)) such        that the midpoint of the PI interval of the voxel        (x_(i),y_(j),z_(ij)) coincides with s_(l). Thus,        (x_(i),y_(j),z_(ij))ϵS(s_(l)), with reference to Eq. 3. Also,        find the top and bottom boundaries of V_(overlap) (s_(l)) above        (x_(i),y_(j)).    -   3) Reconstruct two PARs f⁻ and f₊ using the intervals I⁻(s_(l))        and I⁻(s_(l)), respectively. The PARs will be reconstructed in        the coordinates (x,y,h). These coordinates are converted to        physical coordinates by the formula        (x,y,h)→(x,y,z(x,y,s_(l))+h). The value of his constrained to        the interval |h|<H, where H is sufficiently small so that the        resulting volume is strictly inside of V_(overlap) (s_(l)).    -   4) Perform image registration by finding the shifts {right arrow        over (Δ)}_(ij).

{right arrow over (Δ)}_(ij)=argmin Σ_(ij)[f₊((x _(i) ,y _(j),h=0)+{right arrow over (Δ)}_(ij))−f⁻((x _(i) ,y _(j) ,h=0)−{right arrowover (Δ)}_(ij))]².  (4)

In discussing the geometric meaning of the minimization problem shown inEq. 4, recall that the points (x_(i),y_(j),h=0) all belong to thesurface S(s_(l)). The term f₊((x_(i),y_(j),h=0)+{right arrow over(Δ)}_(ij)) then corresponds to the values of the symmetrically distortedsurface ((x_(i),y_(j),h=0)−{right arrow over (Δ)}_(ij)) inside thevolume f⁻. By solving Eq. 4, it is guaranteed that the values of f₊ andf⁻ on the two distorted surfaces coincide. Once a solution to Eq. 4 isfound, it is assumed that the points on the surface S(s_(l)) moveaccording the following formula:

$\begin{matrix}\left. \left( {x_{i},y_{j},z_{ij}} \right)\rightarrow{\left( {x_{i},y_{j},z_{ij}} \right) + {{\overset{\rightarrow}{\Delta}}_{ij}{\frac{s - s_{l}}{\pi/2}.}}} \right. & (5)\end{matrix}$

Since the sets V_(overlap)(s_(l)) are fairly thin, one option is toregister two surfaces rather than two volumes.

For additional noise stability, it may be required that motion vectors{right arrow over (Δ)}_(ij) two-dimensional, i.e. have zero h-component.This way, Eq. 4 is equivalent to registering two 2D images. The downsideof this approach is that motion away from the surface S(s_(l)) isignored. If motion vectors {right arrow over (Δ)}_(ij) are 3D, then theaccuracy of the motion estimation is increased, but noise stability isdecreased.

Since the problems of Eq. 4 are independent from each other for all l=1,2, . . . , to insure that the estimated motion vectors change smoothlyfrom one l to the next, the problems of Eq. 4 can be combined for all land a regularizer can be added that enforces smoothness of {right arrowover (Δ)}_(ij)(s_(l)) along l.

The third step involves motion-compensated reconstruction. It isproposed that the most straight forward motion compensationreconstruction can be used, wherein motion is accounted for at thebackprojection step. Thus, when reconstructing, all that is necessary isto find where any given voxel is located at the current time. This canbe done by using the following method steps:

-   -   1) Given a voxel (x_(i),y_(j),z_(k)), find its PI line.    -   2) Compute the mid-point s_(mid) of the PI parametric interval        of the voxel. This implies that (x_(i),y_(j),z_(k))ϵS(s_(mid)).        In other words, the potato chip containing the given voxel is        found.    -   3) Find the interval [s_(l), s_(l+1)] containing (s_(mid)).    -   4) Find the motion vector {right arrow over (Δ)}_(ij)(s_(mid))        of the voxel by interpolating between {right arrow over        (Δ)}_(ij)(s_(l)) and {right arrow over (Δ)}_(ij)(s_(l+1)).    -   5) For a given source position/time s, the new position of the        voxel is calculated by using the following formula, with        reference to Eq. 5:

$\begin{matrix}\left. \left( {x_{i},y_{j},z_{k}} \right)\rightarrow{\left( {x_{i},y_{j},z_{k}} \right) + {{{\overset{\rightarrow}{\Delta}}_{ij}\left( s_{mid} \right)}{\frac{s - s_{mid}}{\pi/2}.}}} \right. & (6)\end{matrix}$

With reference to FIG. 6, a method for estimating and compensating formotion by reducing motion artifacts in an image reconstruction fromhelical computed tomography (CT) scan data of an object of interest isprovided 600. The method 600 may be implemented using the data processor135, the radiation source 110 and the radiation detector 125 of FIG. 1.

At a first step 605, the method 600 includes collecting helical computertomography (CT) scan data of an object of interest, wherein the scandata is acquired using a radiation source to generate a cone beam and aradiation detector to detect the cone beam.

Following the collection of scan data, the method continues at step 610by selecting a plurality of center-points along a trajectory of theradiation source, followed by step 615 for identifying, for each of theplurality of center-points, a pair of sections along the trajectory ofthe scan data, wherein a first section of the pair of sections and asecond section of the pair of sections are positioned on opposite sidesof the center-point.

A typical center-point may be denoted s₀, a first section of a pair maybe denoted as I⁻(s₀) and a second section of a pair may be denoted asI₊(s₀). The sections should not be too long, so that the amount ofobject motion during the time the source moves along the section isnegligible. At the same time, the length of the section should not betoo short, so that they would allow incomplete reconstruction of a partof the object of interest such that some of its features are clearlyrecognizable.

In one embodiment, the center-points are equidistant from each otheralong the trajectory scan and the length of the first and secondsections in each pair are equal. In an additional embodiment, thepositions of the center-points do not necessarily have to be uniform andthe lengths of the sections do not have to be equal. For example, thecenter-point positions and lengths of pairs of sections along thetrajectory of the radiation source could be based upon an externalsignal that includes motion information of the object of interest. In anexemplary embodiment, an ECG (electrocardiogram) signal could becollected concurrently with the helical scan data and, during times whenthe cardiac motion of a patient is slow, the center-points could bespaced farther apart, and when the cardiac motion of a patient is fast,the center-points could be spaced closer together. Accordingly, themotion information signal can be used to determine the spacing betweeneach of the plurality of center-points and a location of each of theplurality of center-points. Similarly, when the cardiac motion of apatient is slow, the lengths of the sections in a pair of sections alongthe trajectory can be increased and when the cardiac motion of a patientis fast, the lengths of the sections in a pair of sections along thetrajectory could be decreased. As such, the motion information signalfrom an external source, such as an ECG, could be used to improve themotion estimation and compensation method.

At a next step 620, the method continues by reconstructing, for eachpair of sections, a first partial image from the scan data of the firstsection and a second partial image from the scan data of the secondsection. The image reconstructed using scan data corresponding to I₊(s₀)is denoted as f_(s) ₀ ⁺({right arrow over (x)}) and the imagereconstructed using scan data corresponding to I⁻(s₀) is denoted asf_(s) ₀ ⁻({right arrow over (x)}) The set of points {right arrow over(x)}, where the images are reconstructed should be the same for bothsections. This set of points is denoted as V(s₀). Due to the limitedextent of the detector, the set of points is not too large and isgenerally located in a small neighborhood of lines (chords) connectingpoints on I₊(s₀) with points on I⁻(s₀). In particular, thesereconstructions pertain to a subset of the object of interest. Since thesections of the trajectory I₊(s₀) and I⁻(s₀) generally cover a limitedangular range, reconstructions of f_(s) ₀ ⁺({right arrow over (x)}) andf_(s) ₀ ⁻({right arrow over (x)}) are referred to as Partial AngleReconstructions (PARs). The reconstructions of f_(s) ₀ ⁺({right arrowover (x)}) and f_(s) ₀ ⁻({right arrow over (x)}) do not have to attemptto recover the attenuation coefficient exactly, they can insteadreconstruct a modified image of the object, e.g. with enhanced edges.The main requirement for the reconstruction is that f_(s) ₀ ⁺({rightarrow over (x)}) and f_(s) ₀ ⁻({right arrow over (x)}) be very close toeach other if the object does not have any motion during the scan.

Image registration of the first partial image and the second partialimage is then performed at step 625 to estimate a deformation thattransforms the first partial image into the second partial image,wherein the deformation is representative of motion of the object ofinterest during the scan. In performing the image registration, thedeformation that transforms one image into another is taken to be anestimate of the deformation that the object is undergoing in aneighborhood of the region V(s₀) at the time close to s₀. Byinterpolating motions estimated in regions V(s₀) for all center-pointss₀, a global deformation function is obtained for a region of interestin the object of interest. This deformation function has the propertythat deformation at different points {right arrow over (x)} in theobject is estimated not for all times, but at fixed times, depending onthe time interval when that point was irradiated by the radiationsource.

At step 630, the method concludes by generating a motion compensatedimage by reconstructing the object of interest using the scan data andthe estimated deformation.

As such, in various embodiments, the present invention provides animproved system and method for estimating motion and reducing motionartifacts produced during image reconstruction from helical computedtomography scan data

The above exemplary embodiment is not meant to be limiting andvariations of the exemplary embodiment are within the scope of thepresent invention.

In general, the method is applicable for more general helical-liketrajectories, e.g. variable pitch helices, helices in which the axis ofrotation changes somewhat (e.g., as in thermal drift), etc.

Other methods may also be used for computing PARs. Such methods can bebased on Local Tomography (LT), or exact or quasi-exact reconstruction.

Instead of estimating the motion (or, equivalently, deformation) of theobject, the method can also be used for calibration of the scan (i.e.determination of relevant scan parameters, e.g. position of the centralray, or source-to-center of rotation distance, etc.) In an additionalembodiment, the calibration can be performed on the fly during the scanor subsequent to the scan. The calibration can also be performed byfinding one set of parameters for the entire scan or by computing theseparameters as functions along the scan trajectory.

In various embodiments, the source trajectory may consist ofhelical-like turns in one direction followed by helical-like turns inthe opposite direction.

The proposed method of the present invention can be used in conjunctionwith other motion estimation algorithms. For example, if a preliminarymotion model is obtained using fiducial markers, then the proposedalgorithm can be used as a second step for finding an improved (i.e.more accurate) motion model.

The present invention may be embodied on various computing platformsthat perform actions responsive to software-based methods. The followingprovides an antecedent basis for the information technology that may beutilized to enable the invention.

The computer readable medium described in the claims below may be acomputer readable signal medium or a computer readable storage medium. Acomputer readable storage medium may be, for example, but not limitedto, an electronic, magnetic, optical, electromagnetic, infrared, orsemiconductor system, apparatus, or device, or any suitable combinationof the foregoing. More specific examples (a non-exhaustive list) of thecomputer readable storage medium would include the following: anelectrical connection having one or more wires, a portable computerdiskette, a hard disk, a random access memory (RAM), a read-only memory(ROM), an erasable programmable read-only memory (EPROM or Flashmemory), an optical fiber, a portable compact disc read-only memory(CD-ROM), an optical storage device, a magnetic storage device, or anysuitable combination of the foregoing. In the context of this document,a computer readable storage medium may be any non-transitory, tangiblemedium that can contain, or store a program for use by or in connectionwith an instruction execution system, apparatus, or device.

A computer readable signal medium may include a propagated data signalwith computer readable program code embodied therein, for example, inbaseband or as part of a carrier wave. Such a propagated signal may takeany of a variety of forms, including, but not limited to,electro-magnetic, optical, or any suitable combination thereof. Acomputer readable signal medium may be any computer readable medium thatis not a computer readable storage medium and that can communicate,propagate, or transport a program for use by or in connection with aninstruction execution system, apparatus, or device. However, asindicated above, due to circuit statutory subject matter restrictions,claims to this invention as a software product are those embodied in anon-transitory software medium such as a computer hard drive, flash-RAM,optical disk or the like.

Program code embodied on a computer readable medium may be transmittedusing any appropriate medium, including but not limited to wireless,wire-line, optical fiber cable, radio frequency, etc., or any suitablecombination of the foregoing. Computer program code for carrying outoperations for aspects of the present invention may be written in anycombination of one or more programming languages, including an objectoriented programming language such as Java, C#, C++, Visual Basic or thelike and conventional procedural programming languages, such as the “C”programming language or similar programming languages.

Aspects of the present invention are described with reference toillustrations and/or block diagrams of methods, apparatus (systems) andcomputer program products according to embodiments of the invention. Itwill be understood that each block of the flowchart illustrations and/orblock diagrams, and combinations of blocks in the flowchartillustrations and/or block diagrams, can be implemented by computerprogram instructions. These computer program instructions may beprovided to a processor of a general-purpose computer, special purposecomputer, or other programmable data processing apparatus to produce amachine, such that the instructions, which execute via the processor ofthe computer or other programmable data processing apparatus, createmeans for implementing the functions/acts specified in the flowchartand/or block diagram block or blocks.

These computer program instructions may also be stored in a computerreadable medium that can direct a computer, other programmable dataprocessing apparatus, or other devices to function in a particularmanner, such that the instructions stored in the computer readablemedium produce an article of manufacture including instructions whichimplement the function/act specified in the flowchart and/or blockdiagram block or blocks.

The computer program instructions may also be loaded onto a computer,other programmable data processing apparatus, or other devices to causea series of operational steps to be performed on the computer, otherprogrammable apparatus or other devices to produce a computerimplemented process such that the instructions which execute on thecomputer or other programmable apparatus provide processes forimplementing the functions/acts specified in the flowchart and/or blockdiagram block or blocks.

It should be noted that when referenced, an “end-user” is an operator ofthe software as opposed to a developer or author who modifies theunderlying source code of the software. For security purposes,authentication means identifying the particular user while authorizationdefines what procedures and functions that user is permitted to execute.

It will be seen that the advantages set forth above, and those madeapparent from the foregoing description, are efficiently attained andsince certain changes may be made in the above construction withoutdeparting from the scope of the invention, it is intended that allmatters contained in the foregoing description or shown in theaccompanying drawings shall be interpreted as illustrative and not in alimiting sense.

It is also to be understood that the following claims are intended tocover all of the generic and specific features of the invention hereindescribed, and all statements of the scope of the invention which, as amatter of language, might be said to fall therebetween.

What is claimed is:
 1. A method for estimating and compensating formotion by reducing motion artifacts in an image reconstruction fromhelical computed tomography (CT) scan data of an object of interest, themethod comprising: collecting helical computer tomography (CT) scan dataof an object of interest, wherein the scan data is acquired using aradiation source to generate a cone beam and a radiation detector todetect the cone beam; selecting a plurality of center-points along atrajectory of the radiation source; identifying a plurality of pairs ofsections along the trajectory of the radiation source, wherein each ofthe plurality of pairs of sections is associated with one of theplurality of center-points and wherein a first section of each of thepairs of sections and a second section of each of the pairs of sectionsare positioned on opposite sides of the center-point; selecting a subsetof the plurality of pairs of sections; reconstructing, for each pair ofthe subset, a first partial image from the scan data of the firstsection and a second partial image from the scan data of the secondsection; performing image registration of the first partial image andthe second partial image for each pair of the subset to estimate adeformation that transforms the first partial image into the secondpartial image, wherein the deformation is representative of motion ofthe object of interest during the scan; and generating a motioncompensated image by reconstructing the object of interest using thescan data and the estimated deformation.
 2. The method of claim 1,wherein reconstructing, for each pair of the subset, a first partialimage from the scan data of the first section and a second partial imagefrom the scan data of the second section further comprises,reconstructing the first partial image and the second partial image in aregion of interest having a substantial overlap.
 3. The method of claim2, further comprising identifying at least one chord between the firstsection and the second section and wherein reconstructing, for each pairof the subset, a first partial image from the scan data of the firstsection and a second partial image from the scan data of the secondsection further comprises, reconstructing the first partial image andthe second partial image at a set of points in a neighborhood of atleast one chord.
 4. The method of claim 1, wherein the first section ofeach of the plurality of pairs of sections and the second section ofeach of the plurality of pairs of sections are separated from each otherby an angular distance equal to π.
 5. The method of claim 1, wherein theplurality of center-points are equally spaced along the trajectory ofthe helical CT radiation source.
 6. The method of claim 1, furthercomprising acquiring a motion information signal and wherein a spacingbetween each of the plurality of center-points and a location of each ofthe plurality of center-points is based upon the motion informationsignal.
 7. The method of claim 1, further comprising acquiring a motioninformation signal and wherein a length of the first section and alength of the second section of the subset is increased or decreasedbased upon the motion information signal.
 8. The method of claim 1,wherein performing image registration of the first partial image and thesecond partial image for each pair of the subset to estimate adeformation that transforms the first partial image into the secondpartial image further comprises estimating a deformation of a point inthe object of interest at a point in time, which is inside an intervalof time during which the point was irradiated by the cone beam of theradiation source.
 9. The method of claim 1, wherein generating a motioncompensated image by reconstructing the object of interest using thescan data and the estimated deformation further comprising, estimating adeformation of the object of interest by interpolating the estimates ofdeformations for the subset.
 10. The method of claim 1, wherereconstructing, for each pair of sections of the subset, a first partialimage from the scan data of the first section and a second partial imagefrom the scan data of the second section is based upon Local Tomography(LT), exact reconstruction or quasi-exact reconstruction techniques. 11.The method of claim 2, further comprising identifying at least one chordbetween the first section and the second section for each pair of thesubset and reconstructing the first partial image and the second partialimage of each pair in a neighborhood of the identified chord to generatea two-dimensional first partial image and a two-dimensional secondpartial image and performing image registration using thetwo-dimensional first partial image and the two-dimensional secondpartial image.
 12. The method of claim 2, further comprising identifyinga chord surface between the first section and the second section foreach pair of the subset and reconstructing the first partial image andthe second partial image of each pair in a neighborhood of theidentified chord surface to generate a three-dimensional first partialimage and a three-dimensional second partial image and performing imageregistration using the three-dimensional first partial image and thethree-dimensional second partial image.
 13. A system for estimating andcompensating for motion by reducing motion artifacts in an imagereconstruction from helical computed tomography (CT) scan data of anobject of interest, the method comprising: a memory for storing ahelical computer tomography (CT) scan data of an object of interest; adata processor for estimating and compensating for motion by reducingmotion artifacts in an image reconstruction from the helical computedtomography (CT) scan data of an object of interest, wherein the dataprocessor is adapted for performing the following operations: loadingthe helical CT scan data from the memory; selecting a plurality ofcenter-points along a trajectory of the radiation source; identifying aplurality of pairs of sections along the trajectory of the radiationsource, wherein each of the plurality of pairs of section is associatedwith one of the plurality of center-points and wherein a first sectionof each of the pairs of sections and a second section of each of thepairs of sections are positioned on opposite sides of the center-point;selecting a subset of the plurality of pairs of sections;reconstructing, for each pair of the subset, a first partial image fromthe scan data of the first section and a second partial image from thescan data of the second section; performing image registration of thefirst partial image and the second partial image for each pair of thesubset to estimate a deformation that transforms the first partial imageinto the second partial image, wherein the deformation is representativeof motion of the object during the scan; and generating a motionartifact compensated image by reconstructing the object of interestusing the scan data and the estimated deformation.
 14. One or morenon-transitory computer-readable media having computer-executableinstructions for performing a method of estimating and compensating formotion by reducing motion artifacts in an image reconstruction fromhelical computed tomography (CT) scan data of an object of interest, themethod comprising: collecting helical computer tomography (CT) scan dataof an object of interest, wherein the scan data is acquired using aradiation source to generate a cone beam and a radiation detector todetect the cone beam; selecting a plurality of center-points along atrajectory of the radiation source; identifying a plurality of pairs ofsections along the trajectory of the radiation source, wherein each ofthe plurality of pairs of sections is associated with one of theplurality of center-points and wherein a first section of each of thepairs of sections and a second section of each of the pairs of sectionsare positioned on opposite sides of the center-point; selecting a subsetof the plurality of pairs of sections; reconstructing, for each pair ofthe subset, a first partial image from the scan data of the firstsection and a second partial image from the scan data of the secondsection; performing image registration for each pair of the firstpartial image and the second partial image of the subset to estimate adeformation that transforms the first partial image into the secondpartial image, wherein the deformation is representative of motion ofthe object of interest during the scan; and generating a motion artifactcompensated image by reconstructing the object of interest using thescan data and the estimated deformation.
 15. The media of claim 13,wherein reconstructing, for each pair of the subset, a first partialimage from the scan data of the first section and a second partial imagefrom the scan data of the second section further comprises,reconstructing the first partial image and the second partial image in aregion of interest having a substantial overlap.
 16. The media of claim14, further comprising identifying at least one chord between the firstsection and the second section and wherein reconstructing, for each pairof the subset, a first partial image from the scan data of the firstsection and a second partial image from the scan data of the secondsection further comprises, reconstructing the first partial image andthe second partial image at a set of points in a neighborhood of the atleast one chord.
 17. The media of claim 13, wherein performing imageregistration of the first partial image and the second partial image foreach pair of the subset to estimate a deformation that transforms thefirst partial image into the second partial image further comprisesestimating a deformation of a point in the object of interest at a pointin time, which is inside an interval of time during which the point wasirradiated by the cone beam of the radiation source.
 18. The media ofclaim 13, wherein generating a motion compensated image byreconstructing the object of interest using the scan data and theestimated deformation further comprising, estimating a deformation ofthe object of interest by interpolating the estimate of deformations forthe subset.
 19. The media of claim 14, further comprising identifying achord between the first section and the second section for each pair ofthe subset and reconstructing the first partial image and the secondpartial image of each pair in a neighborhood of the identified chord togenerate a two-dimensional first partial image and a two-dimensionalsecond partial image and performing image registration using thetwo-dimensional first partial image and the two-dimensional secondpartial image.
 20. The media of claim 14, further comprising identifyinga chord surface between the first section and the second section foreach pair of the subset and reconstructing the first partial image andthe second partial image of each pair on the identified chord surface togenerate a three-dimensional first partial image a three-dimensionalsecond partial image and performing image registration using thethree-dimensional first partial image and the three-dimensional secondpartial image.